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Article

The Influence of COVID-19 and Psychosocial Risks on Burnout and Psychosomatic Health Problems in Non-University Teachers in Spain during the Peak of the Pandemic Regressions vs. fsQCA

by
Valentina Gómez-Domínguez
1,
Teresa Gómez-Domínguez
2,
Diego Navarro-Mateu
2 and
María del Carmen Giménez-Espert
3,*
1
Faculty of Education Sciences, International University of Valencia, 46002 Valencia, Spain
2
Department of Specific Educational Needs and Attention to Diversity, Faculty of Education Sciences, Catholic University of Valencia, 46110 Valencia, Spain
3
Department of Nursing, Faculty of Nursing and Chiropody, University of Valencia, 46010 Valencia, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(20), 13030; https://doi.org/10.3390/su142013030
Submission received: 23 September 2022 / Revised: 4 October 2022 / Accepted: 8 October 2022 / Published: 12 October 2022
(This article belongs to the Special Issue Towards Sustainable Living: Perspective from Emotional Education and Psychosocial Risks in Children, Adolescents and Adults)
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Abstract

:
During the COVID-19 pandemic, teachers had to adapt to the changes caused by remote working, experiencing prolonged stress situations that together with psychosocial factors can lead to burnout and psychosomatic health problems. This study focused on analyzing the influence of COVID-19 and psychosocial risks on psychosomatic problems and burnout at the peak of the pandemic in Spain, from March to April 2020. It combined two methodologies, hierarchical regression models (HRM) and qualitative comparative analysis (QCA). The two methodologies demonstrated greater predictive power for psychosocial demand factors (workload and role conflict) on burnout and psychosomatic health problems. In addition, the fsQCA models demonstrated the contribution of job insecurity and the lack of organizational justice, resources and COVID-19 information. These results can be used by educational managers to improve the daily work of teachers, impacting on the quality of teaching, as well as their response to pandemics, which will benefit society.

1. Introduction

The global context created by the COVID-19 pandemic is apparent in stressful situations related to the risk of contagion, fear and anxiety about a new disease, as well as adaptation to new ways of working [1]. Changes in the world economy and work organization took place due to the COVID-19 pandemic in 2020, and as lockdown measures and the obligation to stay at home came into force, a large proportion of the workforce had to work remotely [2].
In Spain, the rapid spread of the virus led the government to declare a nationwide state of emergency in March for fifteen days [3]. There were 231,606 confirmed cases as of 17 May 2020, according to figures provided by the Ministry of Health [4]. These public health measures dictated by governments to combat the spread of the virus, including isolation, quarantine and social distancing, meant that around 10 million students at all levels of education completed their academic courses by distance learning [5]. Teachers had to adapt to the changes arising from remote work, as a result of being forced to conduct classes in a format that was not face-to-face. The educational challenges included maintaining vitality, promoting meaningful learning and relying on teachers’ work in virtual formats. This was an unprecedented challenge, since most teachers had to produce their own learning material to work remotely and simultaneously had to teach their students to work in virtual spaces [6,7]. According to the World Health Organization (WHO) [8], this new disease affects all three components of health (physical, psychological and social), and all sociodemographic levels. Consequently, being confined for several months in the same place and restricted to leaving home only for emergencies leads people to develop symptoms of emotional discomfort and difficulties in their adaptation, such as stress, dissatisfaction, sleep problems, anxiety, fear and worry [9]. Moreover, in the case of teachers, the assignment of new roles other than academic timetables, interacting with parents and tutoring students is linked to an increased workload and is directly related to emotional exhaustion, symptoms of anxiety and depression, resulting in stressful situations [10,11]. Furthermore, good mental and psychological health were important during the COVID-19 pandemic [12].
Stress is linked to psychosocial factors, and the design and management of work and its environment that may cause mental health problems, or social or physical damage to workers’ health [13]. Psychosocial risks are associated with occupational stress, reduced social interaction and the ability to concentrate, and increased physiological pain, heart disease, depression and anxiety [14,15,16]. These and other psychosocial risks may emerge or develop during COVID-19, and if they are not properly evaluated and controlled, may affect performance at work as well as physical and psychological health [17,18]. One of the explanatory models of stress at work that has the most theoretical and empirical support is Karasek’s demand-control model [19], which is based on the balance between the psychological demands of work, such as the workload (both quantitative and qualitative, i.e., the number and complexity of activities), role conflicts (the inability to satisfy conflicting role expectations), lack of organizational justice (the absence of reciprocity in social exchanges) [20], job insecurity (the perceived risk of job loss in the short period of time) [21], and the level of control over these. Social support at work is a psychosocial resource factor provided by the organization’s management, as well as emotional and technical support [22]. Work stress can therefore be considered in terms of the balance between the psychological demands of the job and control over them, and the relationship between demands and resources is decisive in determining the worker’s well-being [19,23]. In addition, the stress caused by excessive demands may lead to employee burnout. However, increased resources may reduce its occurrence [24,25]. Burnout syndrome is defined as a state of mental, emotional and physical exhaustion due to chronic stress [26]. It is important to study, given the increase in burnout in the educational field [27,28,29]. Psychosomatic disorders are psychological disorders that have a physical effect [30]. Examples include back pain, sleep problems, tension headaches and fatigue [31].
Although pandemics have an impact on people’s health and well-being, few studies have addressed the effect of a pandemic on psychosocial risks, as well as its consequences for burnout levels and occupational health [32]. The literature demonstrates that most studies have focused on the pharmacological or biological aspects of the impact of the disease or its treatment [33]. Others have examined the impact of the pandemic from a business or economic point of view [33] and have even been based on research of e-commerce customers [34], while a minority of studies include some reference to stress [35,36,37] but not to burnout. There have been fewer studies in the educational field, which are more oriented towards university teachers and learning through ICT [38,39]. An application was developed to improve access to COVID-19 information in underserved communities [40] and on students and their psychological health [41], while very few studies have highlighted the impact of health crises on a non-university faculty [42]. A crucial factor is the influence of the pandemic on non-university teachers (early childhood, primary and secondary education), who have experienced a significant change in the way their students work, their awareness of the importance of learning and their school future [43], in addition to the influence of resources, information and the impact of COVID-19, on their lives, as well as work and psychosocial risks [44]. There is a lack of studies of teachers, which analyze the influence of COVID-19 (resources, information and impact) and psychosocial risks on burnout and psychosomatic problems during the peak of the COVID-19 pandemic in Spain, highlighting the importance of the present study. Accordingly, this study aims to evaluate how psychosocial risks (job insecurity, workload, lack of organizational justice, role conflicts and social support) and COVID-19-related issues affected teachers’ health and burnout during the peak of the pandemic, using different approaches: hierarchical regression models (HRM) and qualitative comparative analysis (QCA). This research aims to better understand this situation, and to determine measures for improvement that lead to better quality for teachers in their work and their commitment.

2. Materials and Methods

2.1. Sample

This research was performed using 253 non-university teachers aged 24 to 65 years, with a mean age of 41.61 (SD = 9.68), and 78.3% were women and 21.7% were men (see Table 1 for further details). The sample size was calculated based on the most recent data published in the statistical portal of the Government of the Valencian Community for non-university education for the 2020–2021 academic year, according to which the Community employed 80,565 non-university teachers in public, private and chartered schools [45]. Given this population, a sample size of 250 non-university teachers was necessary for a confidence level of 95% and an alpha error of 6.2%. The snowball non-probability convenience sampling strategy was used to recruit non-university teachers, who were invited to fill out an online survey via e-mail. In the online invitation to participate, teachers were given information with a particular emphasis on the study’s aims, the anonymization of the data collected, confidentiality and non-discrimination of participants, thereby respecting the Declaration of Helsinki (World Medical Association, Fortaleza, Brazil, 2013). No incentive to take part in the investigation was offered. Snowball sampling is a method of recruiting study participants who are not easily accessible, as was the case during the lockdown measures to stop the spread of COVID-19 globally [46,47]. The researcher therefore does not directly recruit participants, but instead contacts others who then connect them with the research participants [48]. The data survey process took place at the peak of COVID-19 in Spain between March and April 2020. The participants completed self-completed questionnaires online, in a process lasting 35 min. The inclusion criteria were: (1) being a non-university teacher, (2) being in active employment, (3) giving authorized consent and a commitment to confidentiality in order to participate (Figure 1).

2.2. Method and Variables

This was a cross-sectional design study, including variables such as psychosocial risks, demand, and resource factors (workload, lack of organizational justice, role conflict, job insecurity and social support), the influence of COVID-19, burnout and psychosomatic health problems.
Measures:
The UNIPSICO Battery for the assessment of psychosocial risks in the workplace [20,22]. This instrument showed adequate psychometric properties (Cronbach’s alpha > 0.86) [20] in this study.
The psychosocial demand factors assessed using the UNIPSICO Battery were:
1. Workload scale: this evaluates the number and complexity of activities performed in relation to the time available. The answers are recorded on a five-point Likert scale with anchors of 0 (never) to 4 (very often: every day). It is structured in six items (e.g. “Have you had to do more than one thing at a time?”). The Cronbach’s alpha in this study is 0.77.
2. Lack of organizational justice scale: the lack of organizational injustice is assessed on a Likert-type scale from 0 to 4 (0 = never; 4 = very frequently: every day), (e.g. “I receive little reward in return for the efforts I put into my work.”). The Cronbach’s alpha in this study is 0.88.
3. Role conflict scale: the simultaneous presence of contradictory expectations associated with a role on a Likert-type scale from 0 to 4 (0 = never; 4 = very frequently: every day). It consists of five items (e.g. “How often do you have conflicts with your direct superior?”). The Cronbach’s alpha in this study is 0.78.
4. Job insecurity scale [49]: the subjective perception of the risk of losing one’s job. It comprises five items (e.g. “I feel insecure about the future of my job”) on a 5-point Likert-type scale, ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). The Cronbach’s alpha for this study is 0.91.
The psychosocial resource factors assessed using the UNIPSICO Battery were:
Social support scale: the worker’s perception of emotional and technical support. It comprises six items (e.g. “Do you feel appreciated at work by your peers?”). The Cronbach’s alpha for this study is 0.81.
The consequences of psychosocial risks were evaluated using:
The psychosomatic health problems scale. This evaluates the frequency of psychosomatic problems, and the need for medical support and treatment. It includes eleven items on a Likert-type scale from 0 to 4 (0 = never; 4 = very frequently: every day) (e.g. “Have you had difficulty sleeping?”). The Cronbach’s alpha for this study is 0.88.
Burnout: this was evaluated using the reduced version of the BAT [50]. It consists of 12 items assessing four scales on a Likert-type scale from 0 to 4 (0 = never; 4 = very frequently: every day): burnout (e.g. “I feel mentally exhausted at work”), mental issues (e.g. “ I struggle to find any enthusiasm for my work”), emotional damage (e.g. “I feel unable to control my emotion at work”), and cognitive damage (e.g. “I have trouble staying focused at work”). The Cronbach’s alpha for this study is 0.91.
The influence of COVID-19: an ad hoc instrument developed by the researchers [51] was used to assess different aspects of the medical emergency caused by COVID-19 (resources, information and impact). It comprises 11 items on a Likert-type scale from 1 to 5 (1 = totally disagree, 5 = totally agree).
Resources: these resources were those offered by the health center, regional government, and national government, (e.g. “I feel that my national government has allocated sufficient resources for dealing with COVID-19 in my daily work”) (3 ítems; Cronbach’s α = 0.87), the information provided by the health center, regional government, and national government,( e.g. “I think that in my center I have been given enough information to deal with COVID-19 in my daily work”) (4 ítems; Cronbach´s α = 0.89). Impact on work (workload, labor conflicts, work-related stress, and work related concerns and fears, e.g. “COVID-19 has increased my workload”) (4 ítems; Cronbach´s α = 0.78).

2.3. Statistical Analyses

Basic descriptive analyses (mean, standard deviation) were calculated and two statistical methodologies were used. Hierarchical regression models (HRM) using the IBM SPSS Statistics 24 software package (IBM Corporation, Armonk, NY, USA), and qualitative comparative analysis (QCA) were performed using fsQCA 2.5 [52].
Linear regression methods are based on the individual contribution made by each variable to the outcome. The hierarchical regression model was estimated taking into account psychosocial demand factors (job insecurity, workload, lack of organizational justice and role conflict) (step 1), social support as psychosocial resource factors (step 2), and in the last step, COVID-19-related resources, impact and information variables (step 3). The QCA models were based on intersection logic, and show the combinations of different paths or attributes (variables) that can lead to the same result (equifinality). The analysis establishes the necessary conditions for a given result to occur, and the sufficient conditions, although they do not always have to be present for a given result to occur. QCA models provide the percentage of variance explained, or cases in which the model is fulfilled, the coverage, and goodness-of-fit indicators and the consistency [53,54].
The raw data were collected before performing QCA [53]. First, all the missing values were removed, and variables with values between 0 (not having the feature, totally outside the set, low values) and 1 (with the feature, totally inside the set, high values) were recalibrated. However, three values had to be considered for automatic recalibration in the case of the continuous variables. In the first (0), an observation with this value is completely out of the range (low level of agreement/value, low burnout and psychosomatic health problems in our case); the second (0.5) considers a midpoint, neither inside nor outside the frame (medium level of agreement/value, medium level of burnout and psychosomatic health problems); and the last (1) considers observation completely within the frame (high level of agreement/value, high level of burnout and psychosomatic health problems) [53]. The values of each variable were then recalibrated with the fsQCA 2.5 software [52] taking into account the three thresholds [55]: 10% (low level or all outside the set), 50% (medium level, neither inside nor outside the set) and 90% (high level or all inside the set).
Necessary and sufficient conditions were used for the influence on burnout and psychosomatic health problems of variables associated with psychosocial risks (workload, role conflict, lack of organizational justice, job insecurity and social support, as well as aspects related to COVID-19 resources, information and impact). The fsQCA analysis showed three possible solutions for a sufficient analysis: complex, parsimonious and intermediate [53]. The latter is presented here, as recommended in the literature [53]. The unique coverage expresses the number of observations (variance) that can be explained by a given combination of conditions, but when selecting the most important condition, we must consider the raw coverage [53]. For the necessary analysis and like the sufficient analysis, the consistency shows the condition to explain a particular result (≥0.90) [53].

3. Results

3.1. Descriptive Statistics and Calibration Values

Table 2 shows the most important descriptive statistics and the calibration values of the study variables.

3.2. Hierarchical Regression Models (HRM)

Psychosocial demand factors (job insecurity, workload, lack of organizational justice and role conflict) and social support were included as psychosocial resource factors, and COVID-19-related resources, impact and information variables on burnout and psychosomatic health problems were included in the last step (Table 3). The dependent variables were burnout and psychosomatic health problems. The explanatory variables were psychosocial demand factors (job insecurity, workload, lack of organizational justice and role conflict) (step 1), social support as psychosocial resource factors (step 2), and in the last step, the resource, impact and information variables related to COVID-19 (step 3).
For burnout (R2adjusted = 0.57, p ≤ 0.001), in the first step, the psychosocial demand factors significantly increased the variance by 56% (ΔR2 = 0.56, p ≤ 0.001), including the resource’s psychosocial factor. Social support explained 1% of the variance (ΔR2 = 0.01, p ≤ 0.01), and there was no significant increase in burnout in teachers with the inclusion of the COVID-19-related resource, impact and information variables. In the last step, role conflict (β = 0.42, p ≤ 0.001) and workload (β = 0.31, p ≤ 0.05) informed statistically significant and positive beta coefficients for burnout. For psychosocial resource factors, social support presented a statistically significant and negative beta coefficient (β = −0.14, p ≤ 0.01) and the impact of COVID-19 also demonstrated a statistically significant and positive beta coefficient (β = 0.12, p ≤ 0.05) on burnout among teachers.
For psychosomatic health problems (R2adjusted = 0.50, p ≤ 0.001), the psychosocial demand factors in the first step significantly increased the variance by 47% (ΔR2 = 0.47, p ≤ 0.001). The addition of the resource factor of social support had no effect, while adding the COVID-19-related resource, the impact and information variables in the last step significantly increased the variance by 5% (ΔR2 = 0.05, p ≤ 0.0.001). In this last step, role conflict (β = 0.31, p ≤ 0.001), lack of organizational justice (β = 0.23, p ≤ 0.001) and workload (β = 0.21, p ≤ 0.001) demonstrated statistically significant and positive beta coefficients for psychosomatic health problems. The impact of COVID-19 also demonstrated a statistically significant and positive beta coefficient (β = 0.22, p ≤ 0.001) on psychosomatic health problems in teachers.

3.3. Fuzzy-Set Qualitative Comparative Analysis (fsQCA)

3.3.1. Necessary Condition Analysis

Necessary conditions always have to be present for a specified result to occur [53]. The consistency values must be ≥0.90 for the condition to be considered necessary. Since the consistency values in this study are <0.90 in all cases, none of the conditions can be considered necessary [53].

3.3.2. Sufficiency Analysis

In fsQCA, a model is informative when the consistency is ≥0.75 [56]. In the prediction of the levels of the variables’ burnout and psychosomatic health problems, the three main sufficient conditions according to the Fiss format [57] are presented in Table 4.
Fifteen paths were observed in relation to the high levels of burnout in teachers that explain 80% of the cases (overall consistency = 0.79; overall coverage = 0.80). The most important of these paths was the interaction of role conflict, workload and COVID-19 impact (raw coverage = 0.49; consistency = 0.88), which accounted for 49% of cases with high burnout levels. In the prediction of low levels of burnout, fifteen paths explained 79% of the cases (overall consistency = 0.81; overall coverage = 0.79). The most important path for explaining it was the interaction of lack of job insecurity and lack of organizational justice, and the presence of social support (raw coverage = 0.44; consistency = 0.90), which accounted for 44% of cases with low burnout levels in teachers.
Twenty paths explained 71% of the cases of high levels of psychosomatic problems (overall consistency = 0.80; overall coverage = 0.71). The most important path for explaining high levels of psychosomatic problems were the interaction of role conflict, lack of COVID-19 resources and information, and impact of COVID-19, (raw coverage = 0.40; consistency = 0.91), which accounted for 40% of cases with high levels of psychosomatic problems. Finally, fourteen paths explained 83% of cases of low levels of psychosomatic problems (overall consistency = 0.79; overall coverage = 0.83). The most important path for explaining low levels of psychosomatic problems was the interaction of a lack of role conflict and workload (raw coverage = 0.65; consistency = 0.83), which accounted for 65% of cases with low levels of psychosomatic problems.
A summary of the main results of burnout and psychosomatic health problems using the two methodologies of hierarchical regression modeling (HRM) and qualitative comparative analysis (QCA) is shown in Figure 2 and Figure 3.

4. Discussion

As a global pandemic, COVID-19 has impacted on the societies of the twenty-first century, highlighting their fragility in all areas of life. In this context, teachers have spent more time adapting to this new and complex situation, remote teaching and teleworking [58]. Preschool, primary and secondary school teachers are susceptible to developing psychological exhaustion, manifested through physiological symptoms, which endangers the teaching of their students [24,28,59]. Moreover, exposure to poor working conditions is one of the main stress factors among teachers [60]. Hence the importance of this study, which assessed the influence of COVID-19 (resources, information and impact), and psychosocial risks, demand, and resources (workload, lack of organizational justice, role conflict, job insecurity and social support) on burnout and psychosomatic health problems among teachers at the peak of the pandemic in Spain [61]. To that end, two methodologies were applied: hierarchical regression models (HRM) and qualitative comparative analysis (QCA).
In general, the regression models demonstrated that psychosocial demand factors were predictive of burnout, and especially workload and role conflict in the positive sense. Meanwhile, the psychosocial factor resource of social support did so in a negative sense. These findings are consistent with the literature on the effect of psychosocial demand factors on burnout [24,28,29,59,62]. Overall workload is usually the main contributor to teacher burnout [43,63], and social support as a psychosocial resource can act as a protective factor [64]. Receiving support is one of the most important tools for managing stressors, as this increases personal confidence when dealing with further difficulties [65]. In particular, in the context of academic work, being part of a group is important, as it is related to the creation of a network of reciprocal positive relationships between colleagues, encourages teamwork and mutual help [66]. A supervisor who reinforces their employees and their good ideas and actions is also important [67]. Psychosomatic health problems were positively predicted by psychosocial demand factors, and specifically role conflict, lack of organizational justice and overload. The psychosocial resource factor of social support had no influence but the psychosomatic health problems were predicted by the impact of COVID-19. These aspects are explained according to the literature, as changes in the work environment caused by the COVID-19 pandemic gave teachers an increased workload and caused psychosomatic problems [68]. There was a conflict of roles that did not allow a full and risk-free application of efforts towards a clear objective, without a clear understanding of the functions, doubts and inefficiency appearing, in addition to the requirements of life outside work [69]. There was also a need for training in new technologies [70].
In the fsQCA models, the interaction between workload and role conflict is fundamental in the three main paths that explained the high levels of burnout, in addition to the impact of COVID-19 on burnout in Spanish teachers. These aspects are explained according to the literature by the medical emergency caused by COVID-19, and the insufficient perception of information and resources, which had a major impact on their work [43], as well as the rapid adaptation to new teaching formats, such as teaching online [6,7]. Insufficient perceptions in this respect can lead to burnout. Meanwhile, low levels of burnout were explained by the interaction of a lack of job insecurity and organizational justice, and by social support. Once again, social support is seen to be a protective factor against burnout in teachers, as well as the absence of job insecurity, which has a major impact on their working life, as it reduces the employee’s sense of self-confidence, and can therefore lead to chronic stress and then burnout [71,72]. Moreover, if employees feel unfairly treated by the organization, this has a positive effect not only on a teacher’s loyalty to their school, but also on job satisfaction, morale and the school climate [73].
As for high levels of psychosomatic health problems, the conditions that were the best predictors are role conflict and the impact of COVID-19, as well as the lack of COVID-19 resources and information. These results are consistent with those of other studies that highlighted the lack of resources and information during the COVID-19 pandemic [43,74,75], as influencing teachers’ satisfaction and well-being [76]. The principal conditions for low levels of psychosomatic health problems, were role conflict and workload. In the literature, role conflict and workload are associated with burnout and psychosomatic health problems during the COVID-19 pandemic [77,78]. This has an impact on students’ learning [78]. Like other studies, our results emphasize the importance of resources and information in preventing the impact of COVID-19, burnout and psychosomatic health problems [43,77,78].
Despite this, there have been no previous studies using complementary methodologies, regression models and fsQCA models to assess how COVID-19 (resources, information and impact) and psychosocial risks (job insecurity, workload, lack of organizational justice, role conflict and social support) affected teachers’ health and burnout at the peak of the pandemic. fsQCA models are more predictive than regression models, and provide additional information on variables that that may be useful for preventing burnout and psychosomatic health problems among teachers, such as job insecurity, and a lack of organizational justice, resources and COVID-19 information. These aspects are very important due to the context of non-university teachers’ work at the peak of the pandemic, and the new measures they have had to adopt without the necessary support in terms of information, material and human resources [79]. This is in addition to job insecurity, a factor not analyzed to date [80], which contributes to psychosomatic problems and burnout, predisposing them to poorer physical and mental health, even among the younger members of the study population [81]. Moreover, the literature includes studies with good results for students’ psychological health for various indicators, as well as the relationship between behavior and internal health, including emotional, cognitive and family health [41]. In addition, the education system should reinforce its mental health and psychosocial support for all key stakeholders (teachers, students and family), through either face-to-face or virtual counseling. There were some experiences during the COVID-19 pandemic, which involved developing related health information apps [40] and e-commerce customer research [34]. These findings can be used to implement improvement interventions by education managers and leadership teams in schools. These interventions are focused specifically on social support, taking care of non-university teachers’ social relationships, and enhancing and promoting strong social ties [82], personal self-confidence, flexible scheduling according to individuals’ needs, participation in decision-making and having more academic resources [10,11]. Despite its contribution to the study of the influence of COVID-19 and psychosocial risks to burnout among non-university teachers, the study is not without limitations: it is a cross-sectional study, and as such establishing causal relationships between variables is difficult. Future longitudinal research could establish the relationships between the variables. The characteristics of the participants’ institutions and their location, as well as the characteristics of the participating teachers (experience, subjects, the use of new technologies, the tools provided for virtual classes at the peak of the COVID-19 pandemic and personal experience with the virus) should be considered in future research in order to determine their influence on the results. The results were obtained at the peak of the pandemic, so any generalization to other contexts should be performed with caution.

5. Conclusions

The results obtained provide evidence on the psychosocial risks and psychosomatic health problems among teachers at the peak of the COVID-19 pandemic. Based on the results, improvement interventions could be implemented to help teachers improve their occupational environment, as well as their well-being and methods of coping with the pandemic. These interventions include creating a network of positive reciprocal relationships, workplace activities and opening lines of communication among colleagues, and limiting the demands of the job, by reducing pressure at work and making changes to work procedures, and increasing professional resources, while providing clear job descriptions and working guidelines, and more information and resources. Providing stress training for teachers would also be useful, as well as measures to stabilize contracts to reduce job insecurity among non-university teachers. These aspects will improve their daily work and the quality of teaching, as well as their response to pandemics, which will benefit society.

Author Contributions

Conceptualization, V.G.-D. and D.N.-M.; methodology, M.d.C.G.-E. and T.G.-D.; software, M.d.C.G.-E.; formal analysis, M.d.C.G.-E. and T.G.-D.; investigation, D.N.-M.; resources, V.G.-D. and M.d.C.G.-E.; writing—original draft preparation, D.N.-M., M.d.C.G.-E. and T.G.-D.; writing—review and editing, M.d.C.G.-E. and V.G.-D.; visualization, V.G.-D., D.N.-M. and T.G.-D.; supervision, M.d.C.G.-E.; project administration, V.G.-D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

No formal ethical scrutiny was required for the study on human participants in accordance with the local legislation and institutional requirements. However, after the purpose of the study was explained, each participant signed an informed consent, in accordance with the Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available from the corresponding author upon reasonable request.

Acknowledgments

We would like to thank all the teachers who voluntarily participated in this study.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 14 13030 g001 550
Figure 1. Diagram of the research procedure.
Figure 1. Diagram of the research procedure.
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Figure 2. Main results of burnout.
Figure 2. Main results of burnout.
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Figure 3. Main results of psychosomatic health problems.
Figure 3. Main results of psychosomatic health problems.
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Table
Table 1. Sociodemographic characteristics of the sample.
Table 1. Sociodemographic characteristics of the sample.
Characteristics (n = 253)n%
Sex
Women19878.3
Men5521.7
Educational level
Preschool 3413.4
Primary10039.5
Secondary11947
Employment status
Permanent position16966.8
Substitutes7429.2
Temporary contract104
Level of university studies
Bachelor’s degree16966.8
Master’s degree7429.2
Doctorate degree 104
Table
Table 2. Main descriptive statistics and calibration values.
Table 2. Main descriptive statistics and calibration values.
Role ConflictLack of Organizational JusticeWorkloadJob InsecuritySocial Support COVID-19: ResourcesCOVID-19 InformationCOVID-19 ImpactBurnoutPsychosomatic Problems
M1.061.881.671.892.562.482.612.841.150.96
SD0.700.920.581.120.971.201.211.110.640.61
Min0.000.000.331.000.001.001.001.000.000.00
Max4.003.673.835.004.005.005.005.004.003.20
Calibration values
P100.250.671.001.001.331.001.001.250.500.27
P501.001.831.671.402.502.332.672.751.080.87
P902.053.172.333.603.834.334.334.352.001.73
Note. M = mean; SD = standard deviation; Min = minimum; Max = maximum; P10 = 10th percentile; P50 = 50th percentile; P90 = 90th percentile.
Table
Table 3. Hierarchical regression analysis with the variables of burnout and psychosomatic problems.
Table 3. Hierarchical regression analysis with the variables of burnout and psychosomatic problems.
VariableBurnoutPsychosomatic Problems
PredictorsΔR2βΔR2β
Step 1 0.56 *** 0.47 ***
Job insecurity 0.01 −0.00
Workload 0.30 *** 0.22 ***
Lack of organizational justice 0.06 0.25 ***
Role conflict 0.49 *** 0.35 ***
Step 2 0.01 ** 0.00
Job insecurity −0.01 −0.00
Workload 0.32 *** 0.22 ***
Lack of organizational justice 0.05 0.25 ***
Role conflict 0.44 *** 0.34 ***
Social support −0.13 ** −0.02
Step 3 0.01 0.05 ***
Job insecurity −0.01 −0.03
Workload 0.31 *** 0.21 ***
Lack of organizational justice 0.04 0.23 ***
Role conflict 0.42 *** 0.31 ***
Social support −0.14 ** −0.04
COVID−19: resources −0.04 −0.10
COVID-19: information 0.00 0.70
COVID-19: impact 0.12 * 0.22 ***
Total R2adjusted0.57 *** 0.50 ***
Note. * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.
Table
Table 4. Summary of the three main sufficient conditions for the intermediate solution of burnout and psychosomatic problems.
Table 4. Summary of the three main sufficient conditions for the intermediate solution of burnout and psychosomatic problems.
Frequency Cut-Off: 1 Burnout~BurnoutPsychosomatic Problems~Psychosomatic Problems
Consistency Cut-Off: 0.87Consistency Cut-Off: 0.90Consistency Cut-Off: 0.89Consistency Cut-Off: 0.89
123123123123
Role conflictSustainability 14 13030 i001Sustainability 14 13030 i001Sustainability 14 13030 i001 Sustainability 14 13030 i001 Sustainability 14 13030 i001Sustainability 14 13030 i002Sustainability 14 13030 i002Sustainability 14 13030 i002
WorkloadSustainability 14 13030 i001Sustainability 14 13030 i001Sustainability 14 13030 i001Sustainability 14 13030 i002Sustainability 14 13030 i002 Sustainability 14 13030 i001Sustainability 14 13030 i001Sustainability 14 13030 i002
Lack of organizational justice Sustainability 14 13030 i002 Sustainability 14 13030 i002 Sustainability 14 13030 i001Sustainability 14 13030 i001 Sustainability 14 13030 i002Sustainability 14 13030 i002
Job insecurity Sustainability 14 13030 i002
Social support Sustainability 14 13030 i001 Sustainability 14 13030 i002
COVID-19: resources Sustainability 14 13030 i001Sustainability 14 13030 i001Sustainability 14 13030 i002 Sustainability 14 13030 i002 Sustainability 14 13030 i001
COVID-19: informationSustainability 14 13030 i002 Sustainability 14 13030 i002 Sustainability 14 13030 i002
COVID-19: impact Sustainability 14 13030 i001 Sustainability 14 13030 i002Sustainability 14 13030 i002Sustainability 14 13030 i001Sustainability 14 13030 i001 Sustainability 14 13030 i002
Raw coverage 0.480.470.490.440.380.380.400.350.390.650.460.45
Unique coverage0.020.010.010.030.000.000.010.010.010.060.000.02
Consistency0.850.880.880.900.920.910.910.930.920.830.900.86
Overall solution consistency 0.79 0.81 0.80 0.79
Overall solution coverage 0.80 0.79 0.71 0.83
● = presence of condition, ○ = absence of condition. Expected vector for Burnout: 1,1,1,1,0,0,0,0 (0: absent; 1: present); ~Burnout: 0,0,0,0, 1,1,1,0 (0: absent; 1: present); Psychosomatic problems: 1,1,1,1,0,0,0,1 (0: absent; 1: present); ~Psychosomatic problems: 0,0,0,0, 1,1,1,0 (0: absent; 1: present) using format (Fiss, 2011).
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Gómez-Domínguez, V.; Gómez-Domínguez, T.; Navarro-Mateu, D.; Giménez-Espert, M.d.C. The Influence of COVID-19 and Psychosocial Risks on Burnout and Psychosomatic Health Problems in Non-University Teachers in Spain during the Peak of the Pandemic Regressions vs. fsQCA. Sustainability 2022, 14, 13030. https://doi.org/10.3390/su142013030

AMA Style

Gómez-Domínguez V, Gómez-Domínguez T, Navarro-Mateu D, Giménez-Espert MdC. The Influence of COVID-19 and Psychosocial Risks on Burnout and Psychosomatic Health Problems in Non-University Teachers in Spain during the Peak of the Pandemic Regressions vs. fsQCA. Sustainability. 2022; 14(20):13030. https://doi.org/10.3390/su142013030

Chicago/Turabian Style

Gómez-Domínguez, Valentina, Teresa Gómez-Domínguez, Diego Navarro-Mateu, and María del Carmen Giménez-Espert. 2022. "The Influence of COVID-19 and Psychosocial Risks on Burnout and Psychosomatic Health Problems in Non-University Teachers in Spain during the Peak of the Pandemic Regressions vs. fsQCA" Sustainability 14, no. 20: 13030. https://doi.org/10.3390/su142013030

APA Style

Gómez-Domínguez, V., Gómez-Domínguez, T., Navarro-Mateu, D., & Giménez-Espert, M. d. C. (2022). The Influence of COVID-19 and Psychosocial Risks on Burnout and Psychosomatic Health Problems in Non-University Teachers in Spain during the Peak of the Pandemic Regressions vs. fsQCA. Sustainability, 14(20), 13030. https://doi.org/10.3390/su142013030

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